Otsu Threshold - 2023.1 English

Otsu threshold is used to automatically perform clustering-based image thresholding or the reduction of a gray-level image to a binary image. The algorithm assumes that the image contains two classes of pixels following bi-modal histogram (foreground pixels and background pixels), it then calculates the optimum threshold separating the two classes.

Otsu method is used to find the threshold which can minimize the intra class variance which separates two classes defined by weighted sum of variances of two classes.

Where, w_1is the class probability computed from the histogram.

Otsu shows that minimizing the intra-class variance is the same as maximizing inter-class variance

Where, is the class mean.

API Syntax

template<int SRC_T, int ROWS, int COLS,int NPC=1, int XFCVDEPTH_IN = _XFCVDEPTH_DEFAULT>  OtsuThreshold(xf::cv::Mat<SRC_T, ROWS, COLS, NPC, XFCVDEPTH_IN> & _src_mat, uint8_t &_thresh)

Parameter Descriptions

The following table describes the template and the function parameters.

Resource Utilization

The following table summarizes the resource utilization of the OtsuThreshold function, generated using Vivado HLS 2019.1 tool for the Xilinx Xczu9eg-ffvb1156-1-i-es1 FPGA, to process a grayscale HD (1080x1920) image.

Performance Estimate

The following table summarizes the performance in different configurations, as generated using Vivado HLS 2019.1 tool for the Xilinx Xczu9eg-ffvb1156-1-i-es1, to process a grayscale HD (1080x1920) image.